Reconceptualizing System Usage: An Approach and Empirical Test

规则网络 操作化 构造(python库) 计算机科学 实证研究 功能(生物学) 背景(考古学) 任务(项目管理) 集合(抽象数据类型) 信息系统 选择(遗传算法) 知识管理 审查 数据科学 结构方程建模 人工智能 古生物学 哲学 管理 认识论 机器学习 进化生物学 电气工程 经济 生物 程序设计语言 工程类 法学 政治学
作者
Andrew Burton‐Jones,Detmar W. Straub
出处
期刊:Information Systems Research [Institute for Operations Research and the Management Sciences]
卷期号:17 (3): 228-246 被引量:1000
标识
DOI:10.1287/isre.1060.0096
摘要

Although DeLone, McLean, and others insist that system usage is a key variable in information systems research, the system usage construct has received little theoretical scrutiny, boasts no widely accepted definition, and has been operationalized by a diverse set of unsystematized measures. In this article, we present a systematic approach for reconceptualizing the system usage construct in particular nomological contexts. Comprising two stages, definition and selection, the approach enables researchers to develop clear and valid measures of system usage for a given theoretical and substantive context. The definition stage requires that researchers define system usage and explicate its underlying assumptions. In the selection stage, we suggest that system usage be conceptualized in terms of its structure and function. The structure of system usage is tripartite, comprising a user, system, and task, and researchers need to justify which elements of usage are most relevant for their study. In terms of function, researchers should choose measures for each element (i.e., user, system, and/or task) that tie closely to the other constructs in the researcher's nomological network. To provide evidence of the viability of the approach, we undertook an empirical investigation of the relationship between system usage and short-run task performance in cognitively engaging tasks. The results support the benefits of the approach and show how an inappropriate choice of usage measures can lead researchers to draw opposite conclusions in an empirical study. Together, the approach and the results of the empirical investigation suggest new directions for research into the nature of system usage, its antecedents, and its consequences.
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